1. Field of the Invention
The present invention relates to a pattern generation method for registering handwritten characters or signatures in a pattern recognition system, and a method for updating them in which dynamic programming matching is used to perform pattern learning based on plural inputs of handwritten characters or signature patterns and the pattern thus learned is generated for registering a pattern which possesses the distinguishing features of the writer.
2. Description of the Prior Art
In recent years, there has been a broad-based demand from various sectors of industry for a system that will allow the online recognition of handwritten characters written with no restrictions on the writer's desired style or speed. Handwritten character recognition is attracting attention as a convenient way of inputting handwritten kanji characters into computer systems such as word processors. Ordinary word processors rely on keyboard input, but because this requires special training, it is not always convenient for the ordinary user. Therefore, handwritten character recognition is useful when frequent use is made of word processors, such as for processing of chits and the like. A signature is another good example of cursive handwriting. Signatures are widely used as a way of confirming the identity of individuals, and signature verification has therefore assumed a critical importance for detecting forged signatures. It is therefore necessary to be able to discriminate accurately between genuine and false signatures. Previously this could only be done by a visual examination, but it is now possible to use electronic means to verify the authenticity of a signature by a technique in which the signature is recognized as a pattern of electrical signals and compared with a registered pattern that has been stored in the system beforehand. Verification based on such pattern recognition can provide a considerable improvement in the accuracy with which a signature can be used to confirm the identity of the signer, and is of considerable utility for expanding the range of applications thereof.
Signature verification was disclosed as part of the online method of handwritten character identification described in Japanese Laid-open Patent Application 62-287387. In the method disclosed, dynamic programming matching is used to obtain a distortion function between a registration pattern and an input signature pattern; the use of a registration pattern and an input signature pattern writing pressure information as well as coordinate information also was disclosed by the prior art. As such, this prior art could provide highly accurate signature verification.
Thus, the prior art incorporating writing pressure information as well as coordinate information in the form of time series information and dynamic programming matching for time normalization to obtain the degree of difference also produced quite a high recognition rate. However, a problem was that unless the registration pattern used as the reference standard for signature verification was correctly prepared, the recognition rate decreased.
One way of preventing deterioration in the recognition rate caused by individual variation has been to register a plurality of character patterns or signature patterns and then, during the recognition process, to obtain the degree of difference between an input pattern and the registration patterns, and then take the degree of difference with the registration pattern closest to the input pattern as the degree of difference to that registration pattern. The problem with this method has been that the degree of difference has to be calculated with respect to many patterns, lengthening the recognition time.
Preparing an average pattern that absorbs the variations in a plurality of input patterns would allow a single pattern to be used as the registration pattern. However, with such a method based on a simple average, during the recognition processing there is again the problem of pattern distortion along the time axis leading to a degradation of the writing and writing pressure, making it unsuitable as a registration pattern.
In signature verification, fluctuations in such a registration pattern become a problem when preparing an initial registration pattern that takes individual idiosyncrasies into account, and each time the registration pattern has to be updated because of gradual changes in the signature.
The object of the present invention is to provide a pattern generation method for registering handwriting and a method for updating same that facilitates the obtaining of a registration pattern that accurately reflects the characteristics of an individual handwritten signature.
To achieve this, the present invention comprises the use of dynamic programming matching to obtain a cumulative error among a plurality of input patterns in the form of a distortion function, and using this distortion function to perform shape averaging and time distortion averaging of input patterns. For this, a registration pattern is prepared by the steps of:
multiple inputs of the same handwritten characters in the form of three-dimensional time series information relating to coordinates and writing pressure;
normalization of the position and size of the multiple handwritten character input patterns;
calculation of distortion function for selecting a desired pattern from the multiple input patterns as a reference pattern and obtaining the time distortion function between the reference pattern and another input pattern using dynamic programming matching;
time axis correction for correcting the time axis of each input pattern by means of the distortion function;
averaging the time axis corrected multiple input patterns;
distortion averaging for averaging the multiple distortion functions; and
time distortion correction for correcting the time axis of the shape averaged patterns, using the distortion function average.
The present invention also comprises using the above steps for updating registration patterns. With respect to handwritten character input patterns that change over time, this enables registration patterns to be updated in accordance with gradual changes in input patterns. In this case the multiple input patterns are dealt with as existing registration patterns and as the most recent input patterns, and the patterns are thereby brought up to date in accordance with gradually changing input patterns.
Thus, in accordance with the present invention a plurality of input patterns are normalized, time axis corrected using distortion functions and shape averaged, whereby the input pattern shape (coordinate and writing pressure information) is averaged.
However, if only the shape is averaged the distortion function will cause the time axis to be corrected to the reference pattern time axis, so that the reference pattern will have a major influence on the time series information. However, it is desirable that the registration pattern be one that fully reflects the individual characteristics, with reference also to time series information. To solve this problem, in the present invention the distortion functions themselves are averaged to perform time distortion correction with respect to the time axis of the obtained shape averaged pattern, thereby removing the distortion at the time of the normalization, with the result that pattern variation is corrected for.
Therefore, it thus becomes possible to obtain a virtual registration pattern which contains the signature characteristics in which movement and shape are both corrected for by shape averaging and time averaging, providing a clear, sharp registration pattern, which has not been possible with the conventional simple pattern averaging. Also, in preparing the handwritten character recognition registration pattern, it is possible to prepare and register an optimum pattern with the same method, with the time axis as an arc axis.
In accordance with the present invention the registration pattern can be used to update existing registration patterns and combined with gradually changing input patterns to obtain the latest pattern for use as the registration pattern.
Further features of the invention, its nature and various advantages will be more apparent from the accompanying drawings and the following detailed description of the invention.